Automatic Speech Recognition
Transformers
PyTorch
Arabic
wav2vec2
hf-asr-leaderboard
robust-speech-event
Eval Results (legacy)
Instructions to use phantomcoder1996/wav2vec2-large-xls-r-300m-arabic-colab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phantomcoder1996/wav2vec2-large-xls-r-300m-arabic-colab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="phantomcoder1996/wav2vec2-large-xls-r-300m-arabic-colab")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("phantomcoder1996/wav2vec2-large-xls-r-300m-arabic-colab") model = AutoModelForCTC.from_pretrained("phantomcoder1996/wav2vec2-large-xls-r-300m-arabic-colab") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4b53309c67ffbf6039272aeb0e32d26ce75bbf7a078a9f93ba8ee92d21ced47
- Size of remote file:
- 1.26 GB
- SHA256:
- d301b0dc003793f48ee0176e366100d3ff1756e342cc8d8764492f22f2502f74
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